Image to image translation focuses on the problem of translating a representation of the imaged scene into another. Examples of this process can, for example, be translating from a greyscale representation into an RGB image or translating an aerial photo into a map view of the same area [1]}. In such a translation process, the generator of the network is commonly conditioned on the first representation, i.e. the input signal or distribution, to achieve better translation. This makes the cGAN and the Pix2pix architecture [1]}, as one specific example, better suited for this task than a generator network conditioned on noise, as in the traditional GAN [3]}.
We choose to condition the generator on SAR measurements of the backscatters of the same area from where we wish to generate ALS-based biomass prediction maps.
